摘要
住房按揭贷款市场向来关注借款人学历水平,但有关学历与借款人行为内在关系的研究却相对不足。以住房公积金贷款为例,利用某重点城市2005-2014年住房公积金贷款还款数据,构建Cox比例风险模型,从总体影响、被动逾期、主动逾期、年龄效应等多个维度,对借款人学历与其还款逾期行为之间的联系进行系统性实证检验。研究结果表明,在偿还住房按揭贷款的过程中,高学历借款人的信用水平相对更优,他们的被动逾期和主动逾期行为发生概率均相对更低,并且这一规律在年轻借款人群体中更加明显。因此,商业银行、住房公积金中心等(准)金融机构可以充分利用学历信号在识别借款人信用过程中的上述作用,进一步加强住房按揭贷款风险防控,更好地实现金融服务供需有效匹配,提高授信方资金安全性和受信方金融可得性。
The housing mortgage market has always focused on the level of the borrower’s education,but the research on the relationship between the education and the borrower’s behavior is relatively insufficient. Based on the repayment data of housing provident fund loans in a key city from 2005 to 2014,and from the dimensions of overall impact,passive overdue,active overdue,age effect,etc.,this paper constructs Cox proportional hazards model and conducts a systematic empirical test on the relationship between higher education and delinquency behavior. The results show that in the process of repayment of housing mortgage loans,the credit level of highly educated borrowers is relatively better,the probability of passive overdue and active overdue behaviors of highly educated groups is relatively low. And this rule is more obvious among young borrowers. Commercial banks,housing provident fund centers and other( quasi-) financial institutions can make full use of the education signal in the identification of borrower credit process,further strengthen the housing mortgage risk prevention and control,better match the supply and demand of financial services and improve the security of creditors’ funds and the financial availability of trusted parties.
作者
王先柱
吴义东
吴璟
WANG Xianzhu;WU Yidong;WU Jing(School of Business,Anhui University of Technology,Ma'anshan 243032,China;School of Public Economics&Administration,Shanghai University of Finance and Economics,Shanghai 200433,China;Department of Construction Management,Tsinghua University,Beijing 100084,China)
出处
《浙江工商大学学报》
CSSCI
北大核心
2020年第4期125-137,共13页
Journal of Zhejiang Gongshang University
基金
国家自然科学基金重大研究计划培育项目“应用大数据识别和控制住房公积金扩面风险研究”(91646126)
国家自然科学基金重大研究计划培育项目“基于多维度大数据的住房按揭贷款风险管理决策支持研究”(91546113)
国家自然科学基金面上项目“住房公积金政策性金融功能提升研究”(71874001)
上海财经大学2019年研究生创新基金资助项目(CXJJ-2019-370)。
关键词
住房公积金贷款
还贷逾期
学历
年龄
信用识别
housing mortgage
delinquency
education
signal
credit identification